Real-time Neural Decoding

Real-Time Neural Decoding is a computational framework within the broader category of neural decoding methods that enables the immediate translation of neural signals into interpretable outputs with minimal latency, distinguishing itself by supporting on-the-fly analysis and interaction in brain-computer interface applications.

63

Publications

3.5K

Citations

299

Authors

141

Institutions

Publications per year

2017–2026

32

Authors

299

  1. KV
    Krishna V. Shenoy

    Stanford University, United States

    4 publications · 300 citations

    4

    h-index

  2. VM
    Valeria Mondini

    Graz University of Technology, Austria

    2 publications · 35 citations

    2

    h-index

  3. JM
    Jorge Moll

    D’Or Institute for Research and Education, Brazil

    2 publications · 53 citations

    2

    h-index

  4. AF
    Adeen Flinker

    New York University, United States

    2 publications · 84 citations

    2

    h-index

  5. PN
    Paul Nuyujukian

    Stanford University, United States

    2 publications · 102 citations

    2

    h-index

1–5 of 299

Venues

  1. PLoS ONE

    6 publications · 624 citations

    6

    h-index

  2. Journal of Neural Engineering

    5 publications · 263 citations

    5

    h-index

  3. NeuroImage

    5 publications · 245 citations

    5

    h-index

  4. Neural Computation

    4 publications · 205 citations

    4

    h-index

  5. Frontiers in Neuroscience

    3 publications · 178 citations

    3

    h-index

1–5